NVIDIA, in partnership with various institutions, is advancing quantum computing through new supercomputers and educational initiatives. Researchers, including Mekena Metcalf of HSBC and Alan Aspuru-Guzik of the University of Toronto, use NVIDIA technologies to simplify quantum simulations and detect fraud in digital payments.
NVIDIA is also collaborating with universities to prepare students for the quantum era. New systems are being deployed in Japan and Denmark to further expand the ecosystem for hybrid quantum-classical computing. Additionally, NVIDIA co-sponsored a quantum hackathon and is working with companies like Classiq, QC Ware, ORCA Computing, Infleqtion, qBraid, and BlueQubit to drive quantum computing forward.
Quantum Computing Advancements: NVIDIA and Collaborators Push Boundaries
The field of quantum computing is witnessing significant advancements, with researchers exploring molecules, deploying supercomputers, and building a quantum workforce through academic programs. NVIDIA technologies are at the forefront of these developments, with researchers in Canada and the U.S. utilizing a large language model to simplify quantum simulations that aid in molecular exploration.
Alan Aspuru-Guzik, a professor of chemistry and computer science at the University of Toronto, led the team. They used CUDA-Q, a hybrid programming model for GPUs, CPUs, and the QPUs quantum systems use. The research was conducted on Eos, NVIDIA’s H100 GPU supercomputer. The software developed from this effort will be available for researchers in fields like healthcare and chemistry.
Quantum Machine Learning for Fraud Detection
HSBC, one of the world’s largest banks, has designed a quantum machine learning application capable of detecting fraud in digital payments. The bank’s quantum machine learning algorithm simulated an impressive 165 qubits on NVIDIA GPUs. This is a significant leap considering research papers typically don’t extend beyond 40 of these fundamental calculating units quantum systems use.
HSBC utilized machine learning techniques implemented with CUDA-Q and cuTensorNet software on NVIDIA GPUs to overcome challenges simulating quantum circuits at scale. Mekena Metcalf, a quantum computing research scientist at HSBC, will present her work at the GTC conference.
Preparing the Next Generation for the Quantum Era
In the field of education, NVIDIA is collaborating with nearly two dozen universities to prepare the next generation of computer scientists for the quantum era. The partnership will design curricula and teaching materials around CUDA-Q. Theresa Mayer, vice president for research at Carnegie Mellon University, emphasized the importance of bridging the divide between traditional computers and quantum systems for the future of computing.
NVIDIA also co-sponsored QHack, a quantum hackathon, to help working developers get hands-on with the latest tools. The winning project, developed by Gopal Dahale of Qkrishi, used CUDA-Q to develop an algorithm to simulate a material critical in designing better batteries.
Expanding the Ecosystem for Hybrid Quantum-Classical Computing
Two new systems are being deployed to further expand the ecosystem for hybrid quantum-classical computing. The largest of the two, ABCI-Q at Japan’s National Institute of Advanced Industrial Science and Technology, will be one of the largest supercomputers dedicated to research in quantum computing. It will use CUDA-Q on NVIDIA H100 GPUs to advance the nation’s efforts in the field.
In Denmark, the Novo Nordisk Foundation will lead the deployment of an NVIDIA DGX SuperPOD, a significant part of which will be dedicated to research in quantum computing. These new systems join Australia’s Pawsey Supercomputing Research Centre, which announced it will run CUDA-Q on NVIDIA Grace Hopper Superchips at its National Supercomputing and Quantum Computing Innovation Hub.
Partnerships and Integrations Driving Quantum Computing Forward
Several partnerships and integrations are driving quantum computing forward. Israeli startup Classiq released a new integration with CUDA-Q, allowing high-level functional models to automatically generate optimized quantum programs. QC Ware is integrating its Promethium quantum chemistry package with the just-announced NVIDIA Quantum Cloud.
ORCA Computing, a quantum systems developer based in London, released results running quantum machine learning on its photonics processor with CUDA-Q. Additionally, ORCA was selected to build and supply a quantum computing testbed for the UK’s National Quantum Computing Centre, which will include an NVIDIA GPU cluster using CUDA-Q.
NVIDIA and Infleqtion, a quantum technology company, partnered to bring quantum-enabled solutions to Europe’s largest cyber-defense exercise with NVIDIA-enabled Superstaq software. qBraid, a cloud-based platform for quantum computing, is integrating CUDA-Q into its developer environment. BlueQubit, a California-based company, described how NVIDIA’s quantum technology, used in its research and GPU service, provides the fastest and largest quantum emulations possible on GPUs.
External Link: Click Here For More